A deep-learning model predicts coronary artery calcium (CAC) scores from chest x-rays, improving risk assessment for coronary artery disease.
Key Details
- 1Researchers developed and validated an AI model to predict CAC scores from chest x-rays.
- 2The study analyzed data from 10,230 patients with paired chest x-rays and CAC scores.
- 3Models were trained to classify risk based on CAC thresholds of 0, 100, and 400.
- 4Best performance AUCs were 0.74–0.79 (x-ray only), improving to 0.77–0.82 with clinical variables.
- 5External validation resulted in consistent AUCs of 0.78–0.81, supporting robustness.
Why It Matters
This research demonstrates AI's potential to estimate coronary risk from routine chest x-rays, reducing reliance on CT, lowering costs, and minimizing radiation exposure for cardiovascular risk assessment.
Source
AuntMinnie
Related News
•Radiology Business
AI-Powered Tool Streamlines CT Scan Prioritization in Emergency Departments
An AI-based CT queue system significantly reduces wait times for ED patients by prioritizing scans likely to reveal critical findings.
•Radiology Business
AI Workflow Enables General Radiologists to Match Breast Specialists in Screening
AI-powered workflow helps generalist radiologists detect breast cancer at rates comparable to specialists.
•Radiology Business
LLMs Automate Radiology Report Quality Control, Study Finds
LLM-based systems can rapidly automate radiology report quality control, saving significant manual review time.